We argue for a foundational epistemic claim and a hypothesis about the production and uses of mathematical epidemiological models, exploring the consequences for our political and socio-economic lives. First, in order to make the best use of scientific models, we need to understand why models are not truly representational of our world, but are already pitched towards various uses. Second, we need to understand the implicit power relations in numbers and models in public policy, and, thus, the implications for good governance if numbers and models are used as the exclusive drivers of decision making.

This article discusses the widespread belief that secrecy in science is increasing—and that secrecy in science is ethically problematic. To what extent should we worry about this alleged development? In an introduction it is observed that there is very little hard empirical evidence supporting the belief of increasing secrecy in science. Evidence seems mostly to be of the anecdotal kind. The “purist ideology” of science, in which openness of research figures prominently as normative basis, is revealed as one-sided with respect to accepted practice. Issues of commercialization of science and patenting are discussed, and it is claimed that what is ethically problematic is less related to secrecy than to more general ethical issues regarding the social consequences of scientific knowledge. On the basis of a particular case, an area of scientific research is introduced for which it is claimed that secrecy does constitute a serious problem. This area has been characterized, by Funtowicz and Ravetz, as “postnormal science!’ It is claimed that postnormal science and regulatory science necessitate new institutional mechanisms inside science to tackle ethical dilemmas.